Systems and methods for automatic time gain compensation in a handheld ultrasound imaging system

ABSTRACT

An apparatus and method for automatically calculating and applying time gain compensation in a handheld or hand-carried ultrasonic imaging machine. The apparatus include an autogain unit to calculate the time gain compensation based on a processed ultrasound image. The image is divided into regions, and the image intensity is used to mask regions which satisfy a threshold. Masked regions are used to calculate a gain curve which is then spatially and temporally smoothed. Means are providing for masking entire columns of regions to remove areas where the probe is not in contact. This approach may allow less experienced users to achieve high quality images without the difficult and time-consuming task of manually adjusting the time gain compensation.

FIELD

This invention relates to ultrasound imaging systems. Embodiments of theinvention relate to ultrasound imaging systems that automatically adjusttime gain compensation.

BACKGROUND

Ultrasound imaging systems are a powerful tool for performing real-time,non-invasive imaging procedures in a wide range of medical applications.In a typical ultrasound system, a transducer sends out ultrasoundsignals and receives their echoes. The echoes are processed to producean ultrasound image of the target anatomy.

The quality of the ultrasound image depends on the skill and experienceof the operator. An important and challenging part of acquiringhigh-quality images is adjusting the various imaging parameters.

Ultrasound waves are attenuated as they propagate deeper into thematerial being imaged. This results in darker pixels as the depthincreases. It is desirable that anatomically identical regions bedisplayed with the same brightness regardless of depth. Depth-dependentgain, or time gain compensation (TGC), is applied to correct images.

Time gain compensation is further complicated by the fact that theamount of attenuation depends on frequency: higher frequencies areattenuated more than lower frequencies.

Conventional ultrasound systems have large control interfaces withnumerous controls which allow operators to adjust a wide range ofparameters. For example, time-gain compensation is often adjusted bymanually adjusting a number of mechanical sliders that each adjust thegain for a particular depth range. Operators typically rely on trial anderror to adjust the gains to produce good images.

There is an increasing demand for small portable ultrasound imagingdevices that are still capable of acquiring good quality ultrasoundimages. Increasing portability and simplicity often involves or requiresreducing the number of controls to accommodate smaller screens andsmaller devices. Fewer controls and reduced need for manual adjustmentsalso make it easier for new ultrasound operators to learn how to usesuch smaller devices.

There remains a need for methods and apparatus operable to applyautomatic time gain compensation in real time, particularly on simpleand/or handheld ultrasonic imaging machines.

SUMMARY Advantages

Thus several advantages of one or more aspects are to provide systemsand methods for automatically adjusting time gain compensation for ahandheld ultrasound machine with little or no user intervention. Thismay make it easier for less experienced operators to achieve a highquality image, enabling better and less expensive diagnosis.

These and other advantages of one or more aspect will become apparentfrom a consideration of the ensuing description and accompanyingdrawings.

The description of the invention which follows, together with theaccompanying drawings should not be construed as limiting the inventionto the examples shown and described, because those skilled in the art towhich this invention pertains will be able to devise other forms thereofwithin the scope of the appended claims.

Further aspects and example embodiments are illustrated in theaccompanying drawings and/or described in the following description.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings illustrate non-limiting example embodiments ofthe invention.

FIG. 1 is a schematic diagram of an ultrasound imaging system accordingto an example embodiment.

FIG. 2 is a block diagram of an example autogain unit.

FIG. 3 is a flowchart illustrating an example method for applying anautomatically calculated time gain compensation curve.

FIG. 4 is a flowchart illustrating an example method for automaticallycalculating a time gain compensation curve.

FIG. 5A is an example grayscale ultrasound image.

FIG. 5B is an example grayscale ultrasound image divided into analysisregions.

FIG. 5C is an example matrix of averaged pixel intensities for eachanalysis region.

FIG. 5D is an example matrix of average pixel intensities for eachanalysis region transformed into decibels.

FIG. 5E is an example matrix of average pixel intensities for eachanalysis region of the ultrasound image of FIG. 5A masked with a minimumthreshold.

FIG. 5F is an example gain curve with a desired gain level.

FIG. 5G is a graph depicting an example target gain curve.

FIG. 5H is an example target gain curve, a quadratic curve fit to thetarget gain curve, and upper and lower bounds.

FIG. 5I is an example transition gain curve.

FIG. 5J is an example offset grayscale ultrasound image with an updatedgain curve.

FIG. 6 is a timing diagram of an example embodiment of the presentdisclosure.

DETAILED DESCRIPTION

Throughout the following description, specific details are set forth inorder to provide a more thorough understanding of the invention.However, the invention may be practiced without these particulars. Inother instances, well known elements have not been shown or described indetail to avoid unnecessarily obscuring the invention. Accordingly, thespecification and drawings are to be regarded in an illustrative, ratherthan a restrictive sense.

One aspect of this invention provides a method for automaticallycalculating a time gain compensation for an ultrasound imaging machine.The ultrasound imaging machine is hand-held in some embodiments. Theinvention may also be embodied in apparatus configured to performautomatic time gain compensation as described herein.

FIG. 1 is a schematic diagram of an example ultrasound imaging system.Ultrasound imaging system 100 comprises an ultrasound data acquisitionunit 102 which is coupled to an ultrasound controller 104. Ultrasoundcontroller 104 provides control signals to ultrasound data acquisitionunit 102 to direct the transmission of ultrasound pulses and thereception of ultrasound echoes. Signals representing the ultrasoundechoes are sent to an ultrasound processor 106 which processesultrasound echo data into an ultrasound image and transmits theultrasound image to a display unit 112 for display to a user. Ultrasoundcontroller 104 is also operatively connected to a user interface 104,which allows the user to change settings and interact with the system.Ultrasound controller 104 is also operatively connected to a data store108 operable to store configurations and settings.

Ultrasound processor 106 may, for example, comprise signal processingcircuits (which may include filters, amplifiers and the like) one ormore analog to digital converters (ADCs), a beamformer and the like. Theprinciples behind and a wide variety of suitable constructions forultrasound processor 106 are well understood to those of skill in theart of designing ultrasound machines. Ultrasound data acquisition unit102 may include a suitable transducer, driving circuits echo signaldetection circuits etc. Data acquisition unit 102 includes one or morevariable gain amplifiers that apply time-gain compensation to theultrasound echo signals. The principles behind and a wide variety ofsuitable constructions for ultrasound data acquisition unit 102 are wellunderstood to those of skill in the art of designing ultrasoundmachines.

Ultrasound processor 106 is operatively connected to an automatictime-gain compensation (TGC) unit 110. TGC unit 110 is connected toreceive ultrasound image data for gain analysis. By analysis of theultrasound image data, TGC unit 110 automatically calculates a desirabletime-gain compensation curve. The curve is provided to ultrasoundcontroller 104 which sets the variable-gain amplifier(s) of ultrasounddata acquisition unit 102 to apply the time-gain curve to the ultrasounddata. The time-gain curve may be updated in real-time. In someembodiments the time-gain curve is updated after each ultrasound imageis acquired.

FIG. 2 is a schematic diagram illustrating an automatic TGC unitaccording to one or more aspects of the present disclosure. AutomaticTGC unit 110 may comprises several units: a gain analyzer unit 220, atarget generator unit 204, a spatial smoother unit 206, and a transitiongenerator unit 208. In other embodiments, the functions of automatic TGCunit 110 may be provided by a different arrangement of subunits. Forexample, the functions of some or all subunits may be combined.

A typical ultrasound image may be represented by a two-dimensional arraycomprising multiple lines each comprising multiple samples. The numberof lines is typically on the order of one hundred. The number of samplesin each line is typically on the order of several hundred. In thisdescription the array may be arranged such that the lines form columnsof the array and sets of samples from different lines at the same depthform rows of the array. To produce a single ultrasound image or ‘frame’,multiple transmit and receive events may be performed.

To improve signal to noise ratio, ultrasound lines are often formed bycombining data received at multiple transducer elements. Data receivedfrom multiple transducer elements can be combined by using receivebeamforming, such as delay and sum beamforming. Multiple lines can beproduced for each transmit/receive event by using multiple receivebeamformers. Such beamformers may be implemented in ultrasound processor106 for example.

Once an entire image frame is acquired, the ultrasound data is mapped toa dynamic range suitable for display. It is typically convenient torepresent each point or pixel of the ultrasound image by a pixel valueor ‘greyscale value’ in the range of 0-255. The gamut of possible pixelvalues may include more or fewer than 255 possible values in differentembodiments.

Mapping may involve, for example, applying log compression, or acombination of log compression and linear scaling to raw values outputby a beamformer.

Gain analyzer unit 202 receives an ultrasound image from ultrasoundprocessor 106 and a target representative pixel value from data store108 (the target representative pixel value may be fixed or usersettable). Gain analyzer 202 processes the ultrasound image data todetermine a measure of how pixel values in the ultrasound image tend tovary with depth. Based on this measure, gain analyzer 202 calculates anoffset gain curve. The offset gain curve indicates how gain would needto be increased or decreased at different depths to make the measure ofhow pixel values vary with depth have the desired representative pixelvalues at different depths.

In some embodiments, the offset gain curve is defined by a number ofpoints. The number of points may be predetermined. The number of pointsmay be changed, for example, by selecting a different imaging preset.Each point corresponds to a specified depth. For each point, the offsetgain curve may indicate an amount of change. For example, if arepresentative pixel value at a depth corresponding to one point of theoffset curve is lower than the target representative pixel value thenthe offset gain curve may specify an increase in gain for that point. Ifthe representative pixel value at a depth corresponding to another pointof the offset curve are greater than the target representative pixelvalue then the offset gain curve may specify an increase in gain forthat point. If the representative pixel value at a depth correspondingto still another point of the offset curve is equal to the targetrepresentative pixel value then the offset gain curve may specify nochange in gain for that point. These amounts of change may be applied toadjust a time-gain compensation being applied by ultrasound processor106.

Target generator 204 receives the offset gain curve from gain analyzerunit 202 and a current time-gain curve from storage unit 108.

The offset gain curve and the current time-gain curve may be defined bythe same or different numbers of points. Interpolation (e.g. linearinterpolation) may be applied, if desired to produce an offset gaincurve and/or current time-gain curve defined by the same number ofpoints.

The offset gain curve and the current gain curve are combined to producea rough target gain curve. In some embodiments the offset gain curve (ora multiple of the offset gain curve which, in some embodiments, is amultiple obtained by multiplying by a factor greater than zero and lessthan one) is added to the current gain curve to yield the rough targetgain curve.

Discontinuities in a time-gain curve may result in visual artifacts inthe output image, such as horizontal banding. Vertical spatial smoothingis applied to the time-gain curve to reduce abrupt changes that maycause banding. The degree of smoothing may be adjustable. In theillustrated embodiment, spatial smoother unit 206 receives the roughtarget gain curve from gain analyzer unit 202. Spatial smoother unit 206smooths the rough target gain curve to produce a target gain curve.

For example, spatial smoother 206 may operate by fitting a curve to thepoints that define the rough target gain curve. The fit may be, forexample a linear fit, a polynomial fit (e.g. a quadratic fit) or anothertype of fit. In some embodiments different types of fit may be selectedby changing imaging presets.

The representative pixel value at different depths is determined notonly by the current time-gain compensation curve but also by anystructures that may be present in the volume being imaged. The effect ofimaged structures on the time-gain curve may be reduced by appropriatelycalculating the representative values for different depths and also bytaking into account the statistics of the distribution of pixel valuesat different depths in fitting the a curve to the points that define therough target gain curve.

In an example embodiment, the fitted curve is forced to lie betweenupper and lower bands. These upper and lower bands may be created basedon a statistical metric, for example, the standard deviation of thepixel values in a given row. The fitted curve may be forced to be veryclose to a point at a depth for which the standard deviation is small.The fitted curve may be allowed to deviate more from points at depthsfor which the standard deviation is larger.

In another example embodiment, the upper and lower bands may be createdbased on a predetermined clipping offset from the fitted curve. Thispredetermined clipping offset may be a constant or may vary with depth.If the rough target gain curve is within the upper and lower bands at agiven depth, the value of the rough target gain curve at that depth isused in the target gain curve. If the rough target gain curve is belowthe lower threshold or above the upper threshold, then the appropriatelower or upper threshold value is used at that depth for the target gaincurve. The offset may vary for example from 0-20 dB. With a clippingoffset of 0, the target gain curve is the curve fit to the rough targetgain curve.

Temporal transition generator unit 208 receives the target time-gaincurve from spatial smoother unit 206 and generates a transitiontime-gain curve to smoothly transition over time from the currenttime-gain curve to the target gain curve. The transition gain curve maybe stored in memory and loaded into an analog gain unit of ultrasounddata acquisition unit 102 and/or ultrasound processor 106 to apply gainfor the acquisition of the ultrasound echo data for the next frame.

Temporal transition generator unit 208 may use a weighting factor todetermine how quickly to transition from the current time-gain curve tothe desired target gain curve. This weighting factor may be chosen totrade off the responsiveness of the gain change against the possibilitythat too-rapid changes in the time-gain curve may cause undesirablevisual artifacts.

The weighting factor may be a predetermined constant chosen throughtesting. Alternatively, the weighting factor may be variable. Forexample, the weighting factor may be responsive to a measure of motionof a probe that carries the ultrasound transducer. If the probe ismoving rapidly then the weighting factor may be set such that thetime-gain curve is allowed to change more rapidly. On the other hand, ifthe probe is not moving or is moving only slowly then the weightingfactor may be set such that the time-gain curve is forced to changegradually. For example, a weighting factor of 60% has beenexperimentally determined to provide a good trade-off betweenresponsiveness and jitter.

Temporal transition generator unit 208 may be configured to not makesmall unnecessary changes in the time-gain curve. If the differencesbetween the transition time-gain curve and the current time-gain curveare within a deadband, the analog gain unit may continue to use thecurrent time-gain curve. A typical value for the deadband may be 1 dB.The deadband may, for example, be in the range of 0.5 dB to 3 dB.

In one example embodiment, transition generator unit 208 comprises ainfinite impulse response (IIR) filter.

The time-gain curve is applied in ultrasound data acquisition unit 102.The time-gain curve may be stored in a memory. Additional TCG hardwaremay comprise a digital to analog converter (DAC), a filtering unit, anoperational amplifier, and individual amplifiers for each receivechannel. Digital values from the memory representing the gains to use atdifferent times are input into the DAC. The analog output from the DACis applied to gain-control inputs of the individual amplifiers. After anultrasound pulse is transmitted, the TGC controller loads the next TGCvalue from memory at the appropriate time so that echo signals receivedduring that interval have the correct gain applied.

Operation

FIG. 3 illustrates an example method 300 for automatically calculatingand applying time-gain compensation in real-time.

In operation 302, ultrasound image data is acquired. Operation 302involves transmitting ultrasound energy via an ultrasonic transducer andreceiving reflected ultrasound energy as ultrasound echoes. Theultrasound echoes are detected at the transducer which outputscorresponding ultrasound echo signals.

In operation 304, the ultrasound echo signals are amplified. Theamplification includes applying time-gain compensation according to acurrent time gain curve. In general, the time-gain compensation causesthe amplification to increase with time after transmission of ultrasoundenergy such that later-received ultrasound echo signals (correspondingto ultrasound that has passed through longer distances in the subject)are amplified more than earlier-received ultrasound echo signals.

In operation 306, the ultrasound data is processed and formed into anultrasound image. Operation 306 may, for example, comprise receivebeamforming.

In operation 308, an autogain algorithm is applied to the ultrasoundimage to calculate a new TGC gain curve. The autogain algorithm mayoperate generally as described above, for example.

In operation 310, the new TGC gain is written into memory for the nextacquisition cycle.

FIG. 4 illustrates an example automatic TGC algorithm 400 according toone or more embodiments of the present disclosure.

In operation 402, a grayscale ultrasound image is divided into a numberof regions. In some embodiments the regions each comprise a rectangulararea of the image. In some embodiments, each row and each column of thearray that makes up the image passes through a plurality of the regions.In some embodiments each column (line) of the image passes through threeor more of the regions.

There may be a fixed number of regions or the number of regions may bevaried depending on imaging depth. For example, the regions may eachrepresent a fixed size that scales with imaging depth.

In operation 404, one or more statistical metrics are calculated for thepixels in each region. The statistical metrics may include arepresentative value for pixels in the region. The representative valuemay, for example, comprise an average value, a mean value, or a medianvalue for the pixel values of pixels within the region. In someembodiments extreme pixel values within the region are not included indetermining the representative value. For example, a number of thehighest and/or lowest pixel values may be excluded from the calculationof the representative value.

The statistical metrics may also include a measure of the range ofdifferent pixel values within the region. For example, a standarddeviation of the pixel values may be determined. In one exampleembodiment, the average and standard deviation of pixel values iscalculated for each region.

In operation 406, the grayscale ultrasound image is masked based on oneor more of the statistical metrics. Masking involves excluding zero ormore regions based on criteria relating the statistical metrics. In oneexample embodiment, any regions whose representative value (e.g. averagepixel value) is greater than a masking threshold are masked. The maskingthreshold may be predetermined based on testing, or may vary dependingon an imaging preset.

Masked regions may be said to satisfy an inclusion condition. Theinclusion condition in some embodiments may be expressed as: arepresentative pixel value for a region (which increases with increasingecho strength) is at least equal to a defined threshold.

Non-masked regions are excluded from the calculations. In someembodiments regions for which the statistical metric is between upperand lower thresholds are masked while regions for which the statisticalmetric is outside the range defined between the thresholds may beexcluded from the calculations. In some embodiments the threshold(s) areset to exclude regions having very weak or no ultrasound echoes. In someembodiments the thresholds are also set to exclude regions havinganomalously strong ultrasound echoes.

In operation 408, statistical metrics for masked regions are used tocalculate an image intensity curve. In one embodiment, a point of theimage intensity curve is calculated for each row of regions by averagingthe average pixel values for all masked regions in the row. Additionalmetrics may be calculated for each row, such as the standard deviationof pixel values.

In operation 410, an offset gain curve is calculated. This may be doneby subtracting the target representative pixel value from the imageintensity curve. The target representative pixel value may be apredetermined constant. The target representative pixel value may beselected through testing. Alternatively, the target representative pixelvalue may be selectable or adjustable by the user.

In operation 412, the offset time-gain curve is combined with thecurrent time-gain curve to yield a corrected time-gain curve. This maybe done, for example, by adding all or a fraction of the offsettime-gain curve to the current time-gain curve.

In operation 414, the corrected gain curve is smoothed. Varioussmoothing techniques may be used such as a linear curve fit or apolynomial fit. In one embodiment, a quadratic polynomial fit is used tosmooth the corrected time-gain curve.

In operation 416, the smoothed time-gain curve is temporally smoothed toease the transition. In one embodiment an infinite impulse responsefilter (IIR) is used to transition to the new gain curve

In any of the above embodiments it can be convenient to define areference level and to represent pixel values relative to the referencelevel. In some embodiments pixel values are represented in decibels (dB)relative to the reference level.

FIGS. 5A-5J illustrate various steps of example method 400 of thepresent disclosure.

FIG. 5A is an example grayscale ultrasound image. The ultrasound imagehas been log-compressed so that each pixel is represented by a valuebetween 0 and 255. The image may or may not have had image enhancementapplied.

FIG. 5B depicts the grayscale ultrasound image of FIG. 5A that has beendivided into a number of rectangular regions. In this example, the imagehas been divided into 5 columns and 10 rows of regions. The number ofcolumns and rows of regions may be different in different embodiments.In some embodiments the number of rows and/or columns is adjustedadaptively based on settings for ultrasound acquisition unit 102. Forexample the number of rows of regions may increase as the depth ofultrasound imaging is increased and/or as the frequency of ultrasoundenergy transmitted is increased.

FIG. 5C is an example matrix of the average pixel values of each region

FIG. 5D is an example matrix of the average pixel value of each regiontransformed into decibels. This transformation is dependent on thedynamic range of the pixel values and the noise floor. In the exampleembodiment the transformation involved the computation:

Gain (dB)=Pixel Intensity/255*Dynamic Range (dB)+Noise Floor (dB).

In this example, the noise floor was 8 dB and dynamic range was 60 dB.The deadband was defined by a threshold of 3 dB. A target gain of 24 dBwas desired. The applied gain varied linearly from 15 dB to 33 dB.

FIG. 5E depicts an example matrix where the average pixel intensitiesare masked based on a minimum threshold. In this case, the threshold is11 dB, which removes a region from the leftmost column.

FIG. 5F depicts an example of the averaged row intensities, the targetgain, and the applied gain. In this example, the horizontal axisrepresents gain in decibels while the vertical axis represents depth inmillimeters. The average of each row intensity is represented by an opencircle and connected with a thick line for clarity. The gain applied togenerate the current image is shown as a thin solid line. The targetgain is shown as a dashed line. In the example, the target gain is 24dB.

FIG. 5G depicts an example corrected time-gain curve illustrated by opendiamonds connected by a thick solid line. This curve is an example ofthe type of curve produced by operations 410 and 412 described above.

FIG. 5H is an example of a corrected target time-gain curve, a quadraticcurve fit, a lower and upper boundary curves, and a smoothed targettime-gain curve. The quadratic curve, shown as a dashed line, is fit tothe corrected time-gain curve shown in FIG. 5G. The upper and lowerbounds, shown as dash-dot lines, are generated by applying a clippingoffset to the quadratic fit. The smoothed target time-gain curve, shownas a thick line, is produced by restricting the corrected time-gaincurve to fall between the boundaries.

FIG. 5I depicts an example of a smoothed gain curve, a current gaincurve, and a transition time-gain curve. The smoothed gain curve, shownas a dotted line, is combined with the current gain curve, shown asseries of squares connected by thin line, to produce the transition gaincurve, shown as a thick line.

FIG. 5J depicts an example ultrasound image with an updated time-gaincurve applied.

FIG. 6 is an example timing diagram according to one or more embodimentsof the present disclosure. When the system is first initialized, aninitial predetermined TGC curve stored in memory or in a script isselected based on the imaging preset and loaded into ultrasoundacquisition unit 102. A first frame is acquired using the initial TGCcurve. Once the initial pre-processing produces a log-compressed image,the AutoTGC unit and the post-processing unit operate in parallel. Theupdated time-gain curve from the first frame is stored in memory andloaded into the receiver before the third frame is acquired.

The second frame is also acquired using the initial TGC curve while thefirst frame is being processed. The gain calculation for the secondframe includes the result from the first gain analysis.

In other embodiments, the automatic TGC unit may not analyze everyframe. For example, gain may be analyzed every Nth frame where N is asuitable integer (e.g. if N=10 every 10^(th) frame). This analysisfrequency may be a predetermined constant or may be variable. In thecase of a predetermined constant, the analysis frequency may be selectedand defined with a particular imaging preset. Alternatively, theanalysis frequency may be variable. The analysis frequency may beadjustable by the user in real-time or as a setting. The analysisfrequency may be adjusted to find a balance between performance andpower saving. The analysis frequency could also be adjustedautomatically. For example, the analysis frequency may be increased incases where probe motion is detected or large changes in the image aredetected. This may increase performance by more quickly adapting todifferent imaging situations that result when the probe is move to a newlocation, for example. This may also allow for conserving power whenminimal changes are detected and it is not necessary to change the gainas frequently.

Example Operation

The following describes an example of how the system may be used.

An operator turns on apparatus as described herein and selects animaging preset suitable for an ultrasound examination to be conducted.The imaging preset is associated with a number of parameters that areloaded into the device memory. These parameters may include noise floor,dynamic range, an initial gain curve, a desired gain level, vertical andhorizontal region number, dead zone threshold, transition speed andothers. The initial gain curve is loaded into memory.

When the operator starts imaging, the ultrasound controller sends theinitial gain curve to the analog front end to apply the correct gain atthe appropriate time in the receive cycle. This initial data is thenprocessed in a way familiar to those with ordinary skill in the art intoa log-compressed image.

The autogain unit receives the log-compressed image and calculates theappropriate update gain as a function of time based on the image, thedesired gain level, the initial gain curve and the parameters associatedwith the current imaging preset. If the updated time-gain differs fromthe current time-gain by more than the dead zone threshold, the updatedtime-gain curve is supplied to the analog front end where the updatedtime-gain curve is used for a subsequent acquisition receive cycle.Otherwise, the previous time-gain curve is reused.

When a large change in gain settings are required, for example, when theoperator first places the probe in contact with the patient, the gainwill quickly and smoothly be transitioned over several acquisitioncycles depending on the transition speed without requiring interventionfrom the operator.

In an embodiment with variable transition speed, the transition speedmay be increased when a large change in probe orientation or position isdetected to quickly transition to a more appropriate gain curve. Thetransition speed may be decreased once probe movement is stabilized inorder to reduce stabilize the image and reduce flickering andunnecessary changes. Probe orientation or changes in probe position maybe detected using appropriate sensors (e.g. accelerometers orelectromagnetic or optical or acoustic position sensors) and/or byperforming analysis of received ultrasound images.

While the above description contains many details of exampleembodiments, these should not be construed as essential limitations onthe scope of any embodiment. Many other ramifications and variations arepossible within the teachings of the various embodiments.

INTERPRETATION OF TERMS

Unless the context clearly requires otherwise, throughout thedescription and the

-   -   “comprise”, “comprising”, and the like are to be construed in an        inclusive sense, as opposed to an exclusive or exhaustive sense;        that is to say, in the sense of “including, but not limited to”;    -   “connected”, “coupled”, or any variant thereof, means any        connection or coupling, either direct or indirect, between two        or more elements; the coupling or connection between the        elements can be physical, logical, or a combination thereof;    -   “herein”, “above”, “below”, and words of similar import, when        used to describe this specification, shall refer to this        specification as a whole, and not to any particular portions of        this specification;    -   “or”, in reference to a list of two or more items, covers all of        the following interpretations of the word: any of the items in        the list, all of the items in the list, and any combination of        the items in the list;    -   the singular forms “a”, “an”, and “the” also include the meaning        of any appropriate plural forms.

Words that indicate directions such as “vertical”, “transverse”,“horizontal”, “upward”, “downward”, “forward”, “backward”, “inward”,“outward”, “vertical”, “transverse”, “left”, “right”, “front”, “back”,“top”, “bottom”, “below”, “above”, “under”, and the like, used in thisdescription and any accompanying claims (where present), depend on thespecific orientation of the apparatus described and illustrated. Thesubject matter described herein may assume various alternativeorientations. Accordingly, these directional terms are not strictlydefined and should not be interpreted narrowly.

Embodiments of the invention may be implemented using specificallydesigned hardware, configurable hardware, programmable data processorsconfigured by the provision of software (which may optionally comprise“firmware”) capable of executing on the data processors, special purposecomputers or data processors that are specifically programmed,configured, or constructed to perform one or more steps in a method asexplained in detail herein and/or combinations of two or more of these.Examples of specifically designed hardware are: logic circuits,application-specific integrated circuits (“ASICs”), large scaleintegrated circuits (“LSIs”), very large scale integrated circuits(“VLSIs”), and the like. Examples of configurable hardware are: one ormore programmable logic devices such as programmable array logic(“PALs”), programmable logic arrays (“PLAs”), and field programmablegate arrays (“FPGAs”)). Examples of programmable data processors are:microprocessors, digital signal processors (“DSPs”), embeddedprocessors, graphics processors, math co-processors, general purposecomputers, server computers, cloud computers, mainframe computers,computer workstations, and the like. For example, one or more dataprocessors in a control circuit for a device may implement methods asdescribed herein by executing software instructions in a program memoryaccessible to the processors.

While processes or blocks are presented in a given order, alternativeexamples may perform routines having steps, or employ systems havingblocks, in a different order, and some processes or blocks may bedeleted, moved, added, subdivided, combined, and/or modified to providealternative or subcombinations. Each of these processes or blocks may beimplemented in a variety of different ways. Also, while processes orblocks are at times shown as being performed in series, these processesor blocks may instead be performed in parallel, or may be performed atdifferent times.

In addition, while elements are at times shown as being performedsequentially, they may instead be performed simultaneously or indifferent sequences. It is therefore intended that the following claimsare interpreted to include all such variations as are within theirintended scope.

Certain aspects of the invention may also be provided in the form of aprogram product. The program product may comprise any non-transitorymedium which carries a set of computer-readable instructions which, whenexecuted by a data processor, cause the data processor to execute amethod of the invention. Program products according to the invention maybe in any of a wide variety of forms. The program product may comprise,for example, non-transitory media such as magnetic data storage mediaincluding floppy diskettes, hard disk drives, optical data storage mediaincluding CD ROMs, DVDs, electronic data storage media including ROMs,flash RAM, EPROMs, hardwired or preprogrammed chips (e.g., EEPROMsemiconductor chips), nanotechnology memory, or the like. Thecomputer-readable signals on the program product may optionally becompressed or encrypted.

In some embodiments, some aspects of the invention may be implemented insoftware. For greater clarity, “software” includes any instructionsexecuted on a processor, and may include (but is not limited to)firmware, resident software, microcode, and the like. Both processinghardware and software may be centralized or distributed (or acombination thereof), in whole or in part, as known to those skilled inthe art. For example, software and other modules may be accessible vialocal memory, via a network, via a browser or other application in adistributed computing context, or via other means suitable for thepurposes described above.

Where a component (e.g. a software module, processor, assembly, device,circuit, etc.) is referred to above, unless otherwise indicated,reference to that component (including a reference to a “means”) shouldbe interpreted as including as equivalents of that component anycomponent which performs the function of the described component (i.e.,that is functionally equivalent), including components which are notstructurally equivalent to the disclosed structure which performs thefunction in the illustrated exemplary embodiments of the invention.

Specific examples of systems, methods and apparatus have been describedherein for purposes of illustration. These are only examples. Thetechnology provided herein can be applied to systems other than theexample systems described above. Many alterations, modifications,additions, omissions, and permutations are possible within the practiceof this invention. This invention includes variations on describedembodiments that would be apparent to the skilled addressee, includingvariations obtained by: replacing features, elements and/or acts withequivalent features, elements and/or acts; mixing and matching offeatures, elements and/or acts from different embodiments; combiningfeatures, elements and/or acts from embodiments as described herein withfeatures, elements and/or acts of other technology; and/or omittingcombining features, elements and/or acts from described embodiments.

It is therefore intended that the following appended claims and claimshereafter introduced are interpreted to include all such modifications,permutations, additions, omissions, and sub-combinations as mayreasonably be inferred. The scope of the claims should not be limited bythe preferred embodiments set forth in the examples, but should be giventhe broadest interpretation consistent with the description as a whole.

What is claimed is:
 1. An ultrasound imaging method comprising:acquiring ultrasound data by transmitting ultrasound signals andreceiving ultrasound echo signals and amplifying the ultrasound echosignals according to gains that vary with echo delay times according toa current time-gain curve; processing the ultrasound data to yield anultrasound image comprising a plurality of rows and columns, the rows ofthe ultrasound image associated with corresponding echo delay times;determining a time-gain compensation curve by: determining arepresentative pixel value for each of a plurality of regions of theultrasound image, the regions arranged in a plurality of rows each ofthe plurality of rows of regions comprising a plurality of the regions,wherein a plurality of rows of the ultrasound image each extend throughthe plurality of regions of a different one of the rows of regions; foreach of the plurality of rows of regions combining those of therepresentative values which satisfy an inclusion condition into acombined representative value associated with a corresponding echo delaytime; for the combined representative values determining correspondinggain offset amounts by which the gains of the time-gain curve differfrom desired gains for the corresponding echo delay times; based on thegain offset amounts adjusting the time-gain curve to more nearly providethe desired gains for the corresponding echo delay times.
 2. A methodaccording to claim 1 wherein the representative values comprise averagepixel values.
 3. A method according to claim 1 wherein the inclusioncondition comprises the representative value exceeding a threshold.
 4. Amethod according to claim 1 wherein adjusting the time-gain curvecomprises combining the offset values with the time-gain curve to yielda target time gain curve.
 5. A method according to claim 4 comprisingspatially smoothing the target time gain curve.
 6. A method according toclaim 5 wherein spatially smoothing the target time-gain curve comprisesfitting a function to the target time gain curve.
 7. A method accordingto claim 6 wherein the function is a linear or polynomial function.
 8. Amethod according to claim 6 comprising determining measures of thedistributions of different pixel values within some or all of theregions and fitting the function is based on the measures of thedistributions.
 9. A method according to claim 8 wherein the measures ofthe distributions comprise standard deviation.
 10. A method according toclaim 9 repeated for a plurality of temporally spaced-apart frames, themethod comprising temporally smoothing changes in the time-gain curve.11. A method according to claim 10, wherein temporally smoothingcomprises processing gain values by a temporal filter.
 12. A methodaccording to claim 11 wherein the temporal filter comprises an infiniteimpulse response filter.
 13. A method according to claim 11 whereintransmitting ultrasound signals and receiving ultrasound echo signals isperformed using a probe and the method comprises monitoring motions ofthe probe and adjusting the temporal filter based on the motions of theprobe.
 14. A method according to claim 13 comprising controlling thetemporal filter to have a higher time constant when the probe is movingless and controlling the temporal filter to have a lower time constantwhen the probe is moving more.
 15. A method according to claim 1 whereinthe regions are arranged to provide at least four rows with at leastthree regions in the four rows.
 16. A method according to claim 15comprising automatically changing a number of rows of the regions basedon a setting of an ultrasound depth control.
 17. A method according toclaim 1 wherein each of the regions has a height of 2 or more rows ofthe ultrasound image and a width of at least 2 columns of the ultrasoundimage.
 18. A method according to claim 1 comprising if all of the gainoffset amounts are within a deadzone, suppressing adjusting thetime-gain curve.
 19. A method according to claim 1 comprising repeatingacquiring ultrasound data to obtain a sequence of ultrasound frames,wherein one or more of the sequence of ultrasound frames is acquiredbetween obtaining the ultrasound image data and adjusting the time-gaincurve.
 20. A method according to claim 1 wherein determining the gainoffset amounts comprises comparing the combined representative values toa target representative value.
 21. An ultrasound imaging systemcomprising: an ultrasound data acquisition unit comprising an ultrasoundtransducer, an ultrasound transmitter connected to drive the transducerto emit ultrasound signals; and an ultrasound receiver connected todetect echo signals picked up by the ultrasound transducer; a pluralityof variable gain amplifiers connected to amplify the echo signalsaccording to a variable time-gain curve; a beamformer connected toprocess the amplified echo signals to yield an ultrasound image, theultrasound image comprising a plurality of rows and columns, the rows ofthe ultrasound image associated with corresponding echo delay times;and, a processor configured by software instructions in a memoryoperatively coupled to the processor to perform an autogain routine, theautogain routine operative to process the ultrasound image to yieldcorrections to the time-gain curve and to apply the corrections to thetime-gain curve wherein the autogain routine comprises: determining arepresentative pixel value for each of a plurality of regions of theultrasound image, the regions arranged in a plurality of rows each ofthe plurality of rows of regions comprising a plurality of the regions,wherein a plurality of rows of the ultrasound image each extend throughthe plurality of regions of a different one of the rows of regions; foreach of the plurality of rows of regions combining those of therepresentative values which satisfy an inclusion condition into acombined representative value associated with a corresponding echo delaytime; for the combined representative values determining correspondinggain offset amounts by which the gains of the time-gain curve differfrom desired gains for the corresponding echo delay times; and based onthe gain offset amounts adjusting the time-gain curve to more nearlyprovide the desired gains for the corresponding echo delay times.
 22. Amethod for producing a time gain compensation curve based on agrey-scale ultrasound image, the method comprising: dividing thegrey-scale image into a plurality of regions arranged in a plurality ofrows; calculating a mean pixel intensity for pixels within each of theregions; masking those of the regions for which the mean pixel intensityis less than a threshold; calculating a mean of unmasked regions foreach of the plurality of rows of regions to form a gain curvesubtracting a desired gain from the gain curve to yield an offset gaincurve combining the offset gain curve with a current gain curve to yieldan updated gain curve; smoothing the updated gain curve; and applying atemporal filter to the smoothed updated gain curve.
 23. The method ofclaim 22, wherein the curve smoothing applied in step g, is selectedfrom the group consisting of linear and quadratic.